All Reports
Flask
Python
pallets/flask
Pass Rate
37%
The Python micro framework for building web applications
L1100%
L285%
L30%
L40%
L50%
Strong Testing
Flask reaches Level 2 with 57% Testing pass rate. Currently building team readiness with 23/62 criteria passing (37%). Key areas for improvement include the opportunities listed below.
Strengths
01
Formatter
Ruff format configured in pyproject.toml and ruff-format hook in pre-commit config.
02
Lint Config
Ruff linter configured in pyproject.toml with select rules (B, E, F, I, UP, W) for code quality enforcement.
03
Pre Commit Hooks
.pre-commit-config.yaml configured with ruff, ruff-format, uv-lock, and pre-commit-hooks for automated checks.
Opportunities
01
Cyclomatic Complexity
No cyclomatic complexity analysis found (no lizard, radon, or complexity rules in ruff configuration).
02
Dead Code Detection
No dead code detection tooling found (vulture reference in uv.lock is just a lock entry, no actual configuration).
03
Duplicate Code Detection
No duplicate code detection found (no jscpd, PMD CPD, or similar tooling configured).
All Criteria
Style & Validation5/11 (45%)
—code_modularizationSmall Python library where module boundaries are not complex enough to require enforcement tooling.
✗cyclomatic_complexityNo cyclomatic complexity analysis found (no lizard, radon, or complexity rules in ruff configuration).
✗dead_code_detectionNo dead code detection tooling found (vulture reference in uv.lock is just a lock entry, no actual configuration).
✗duplicate_code_detectionNo duplicate code detection found (no jscpd, PMD CPD, or similar tooling configured).
✓formatterRuff format configured in pyproject.toml and ruff-format hook in pre-commit config.
✗large_file_detectionNo large file detection tooling found (no Git hooks checking file size, no CI job flagging large files, no LFS configuration, no linter rules for file size).
✓lint_configRuff linter configured in pyproject.toml with select rules (B, E, F, I, UP, W) for code quality enforcement.
—n_plus_one_detectionFlask is a web framework library without ORM/database layer, N+1 detection not applicable.
✗naming_consistencyNo naming convention enforcement found (no ruff naming rules, no explicit naming conventions documented in AGENTS.md or CONTRIBUTING).
✓pre_commit_hooks.pre-commit-config.yaml configured with ruff, ruff-format, uv-lock, and pre-commit-hooks for automated checks.
✓strict_typingmypy strict mode enabled in pyproject.toml (strict=true) for maximum type safety.
✗tech_debt_trackingNo tech debt tracking tooling found (no TODO/FIXME scanner in CI, no linter rules requiring linked tickets, no SonarQube/SonarCloud configuration).
✓type_checkmypy configured in pyproject.toml with strict=true for strict type checking, also pyright configured.
Build System6/13 (46%)
✗agentic_developmentNo evidence of agent co-authorship in git history (checked last 100 commits for 'droid', 'claude', 'co-author' patterns).
✗automated_pr_reviewNo automated PR review generation found. CI runs status checks but doesn't generate review comments.
✓build_cmd_docREADME.md documents installation and usage. Development setup documented via examples and documentation directory.
✗build_performance_trackingNo explicit build performance tracking found (no build metrics exported, no build caching analysis, no timing instrumentation).
—dead_feature_flag_detectionNo feature flag infrastructure exists, so dead flag detection is not applicable.
✓deployment_frequencyMultiple releases per year detected (30+ releases in recent history), indicating frequent deployment cadence with automation via GitHub Actions publish workflow.
✓deps_pinnedDependencies pinned via uv.lock file committed to repository, ensuring reproducible builds.
✓fast_ci_feedbackCI checks complete in ~1 minute based on statusCheckRollup analysis (pre-commit check: 17-35 seconds, tests: similar duration), well under 10 minute threshold.
✗feature_flag_infrastructureNo feature flag infrastructure found (no LaunchDarkly, Statsig, Unleash, GrowthBook, or custom feature flag system).
—heavy_dependency_detectionNot a bundled frontend application, bundle size analysis not applicable for Python library.
—monorepo_toolingNot a monorepo - single application repository without separate packages requiring monorepo tooling.
—progressive_rolloutNot applicable for a Python library (no deployment infrastructure, no canary/percentage-based rollout configuration).
✓release_automationGitHub Actions publish workflow (.github/workflows/publish.yaml) automates releases on tag push, including PyPI publishing and GitHub release creation.
✗release_notes_automationCHANGES.rst exists but no automation detected (no semantic-release, standard-version, changesets, or release-please configuration).
—rollback_automationNot applicable for a Python library (no deployment infrastructure requiring rollback capability).
✗single_command_setupNo single command setup documented in README or AGENTS.md. Setup requires multiple steps and isn't clearly documented as a single command.
✗unused_dependencies_detectionNo unused dependencies detection found (no depcheck, deptry, pip-extra-reqs, or similar tooling).
✓vcs_cli_toolsGitHub CLI (gh) is available and authenticated (verified via 'gh auth status'), enabling advanced repository operations.
—version_drift_detectionNot a monorepo - single application repository without multiple packages that could have version drift.
Testing4/7 (57%)
—flaky_test_detectionNo explicit flaky test detection tooling found (no test retry configuration, no flaky test tracking tools).
✗integration_tests_existNo integration tests found (no cypress, playwright, selenium, or behave configuration detected).
✓test_coverage_thresholdsCoverage configuration in pyproject.toml ([tool.coverage.run] with branch=true and source specification) enforces coverage standards.
✗test_isolationNo explicit test isolation enforcement found (no pytest-xdist for parallel execution, no test sharding configured).
✓test_naming_conventionspytest naming conventions enforced (testpaths=['tests'] in pyproject.toml, test_*.py pattern followed).
✗test_performance_trackingNo test performance tracking found (no test timing output flags, no test analytics platform integration).
✓unit_tests_existtests/ directory with extensive test coverage (482 tests collected via pytest).
✓unit_tests_runnableTests runnable via pytest (verified with --collect-only, 482 tests collected successfully).
Documentation3/6 (50%)
✗agents_mdNo AGENTS.md file found in repository root to document AI agent essentials.
—agents_md_validationAGENTS.md doesn't exist, so validation is not applicable.
—api_schema_docsFlask is a framework library, not a service with API endpoints requiring OpenAPI/GraphQL schema.
✓automated_doc_generationSphinx documentation generation configured in tox (docs env) and automated via tooling, generates docs from source.
✓documentation_freshnessREADME.md and docs/contributing.rst modified within last 180 days, indicating active documentation maintenance.
✓readmeREADME.md exists at repository root with setup/usage instructions, examples, and links to documentation.
✗service_flow_documentedNo architecture diagrams found (no .mermaid, .puml, .plantuml files, no docs/architecture* or docs/diagrams* directories).
✗skillsNo skills directories found (.factory/skills/, .skills/, .claude/skills/ all absent).
Dev Environment1/3 (33%)
✗database_schemaschema.sql found only in examples/tutorial (not core library). Flask itself doesn't have database schema as it's a framework.
✓devcontainer.devcontainer/devcontainer.json configured with Python image and VS Code settings for development environment.
—devcontainer_runnableDevcontainer CLI validation skipped as not explicitly requested.
✗env_templateNo .env.example file and no environment variables documented in README or AGENTS.md.
—local_services_setupLibrary doesn't have external service dependencies requiring docker-compose for local development.
Debugging & Observability1/8 (13%)
✗alerting_configuredNo alerting configured (no PagerDuty, OpsGenie, or custom alerting rules found).
—circuit_breakersFlask is a library without external service dependencies requiring circuit breaker patterns.
—code_quality_metricsRequires GitHub admin API access to verify code quality metrics (skipped).
✗deployment_observabilityNo deployment observability links found (no Datadog, Grafana, New Relic dashboard references in docs or code).
✗distributed_tracingNo distributed tracing infrastructure found (no OpenTelemetry, no X-Request-ID/trace_id propagation).
✗error_tracking_contextualizedNo error tracking configured (no Sentry, Bugsnag, or Rollbar found in dependencies or configuration).
—health_checksFlask is a library, not a deployed service requiring health check endpoints.
✗metrics_collectionNo metrics/telemetry instrumentation found (no Datadog, Prometheus, New Relic, CloudWatch, or OpenTelemetry).
—profiling_instrumentationProfiling instrumentation not applicable for a library (users profile their own applications built with Flask).
✗runbooks_documentedNo runbook/playbook references found in README, AGENTS.md, or docs/ (only false positives in LICENSE files).
✓structured_loggingDedicated logging module exists (src/flask/logging.py) with structured logging capabilities using Python's logging library.
Security1/8 (13%)
—automated_security_reviewRequires GitHub admin API access to verify automated security review (skipped).
✓branch_protectionGitHub rulesets active protecting main and stable branches (deletion prevention, non-fast-forward prevention verified via API).
✗codeownersNo CODEOWNERS file found in root or .github/ directory.
—dast_scanningFlask is a library, not a deployed web service requiring DAST scanning.
✗dependency_update_automationNo Dependabot or Renovate configuration found in repository.
✗gitignore_comprehensive.gitignore exists but doesn't explicitly exclude .env files (only excludes .idea, .vscode, __pycache__, dist, .coverage, etc).
✗log_scrubbingNo log sanitization/scrubbing mechanisms found in logging configuration (no redaction support, no PII filtering patterns).
—pii_handlingFlask is a framework library that doesn't directly process user data, PII handling is responsibility of applications using Flask.
—privacy_complianceNot applicable for a framework library without direct end-user data collection.
—secret_scanningRequires GitHub admin API access to verify secret scanning configuration (skipped).
✗secrets_managementNo secrets management infrastructure found (no cloud secrets manager integration, no SOPS/age, .env properly gitignored but no .env.example template).
Task Discovery2/4 (50%)
✗backlog_healthOnly 50% of open issues have descriptive titles (>10 chars) AND at least one label, below 70% threshold.
✗issue_labeling_systemInsufficient labeling system (only 1 type label found, no priority labels like P0-P3/critical/high/medium/low, no area labels like frontend/backend/infra).
✓issue_templates.github/ISSUE_TEMPLATE/ exists with bug-report.md and feature-request.md templates.
✓pr_templates.github/pull_request_template.md exists with sections for description, testing, and changelog entry.
Product & Analytics0/2 (0%)
✗error_to_insight_pipelineNo error-to-insight pipeline found (no Sentry-GitHub integration, no error-to-issue automation configured).
✗product_analytics_instrumentationNo product analytics found (no Mixpanel, Amplitude, PostHog, Heap, or GA4 instrumentation).